The prior art distinguishes between active and passive triangulation methods for depth determination. As opposed to passive triangulation methods, active triangulation methods exhibit structured object illumination, where the geometric characteristics of the object illumination are known. Passive methods typically use diffused daylight or spotlights as the object illumination, with at least two camera systems capturing in each case one image of the test object from different viewing directions. What is crucial is that image points that correspond in the at least two captured images are detected. Two image points are considered to be corresponding to one another if they represent the same point on the surface of the test object. The identification of corresponding image points is referred to as correspondence problem.
In active triangulation methods, the correspondence problem is mitigated. In active triangulation methods, a pattern is projected onto the surface of the test object from one specified and previously known spatial direction and is captured from a different spatial direction. Due to the curved surface of the test object, the captured pattern is distorted or deformed. It is possible to reconstruct the three-dimensional structure of the test object (depth determination) from the distortion or deformation of the pattern using appropriate algorithms.
For depth determination it is necessary for distinct features in the projected pattern to be uniquely identified in the captured, deformed or distorted pattern. If said uniqueness is not present or insufficient, the result is skips in the reconstructed three-dimensional structure of the test object.
For the purposes of improvement, the prior art suggests coded or color-coded triangulation methods. One disadvantage of the preferred color-coded triangulation methods is that, owing to absorption, color differences between the projected and captured patterns arise, which in turn lead to skips and consequently a correspondence problem. With correspondingly adapted algorithms during the evaluation of the captured pattern, an attempt is made using smoothing algorithms to interpolate said skips and/or to repair them. This is only insufficiently successful based on the prior art.
In particular in the case of surfaces which absorb colors very differently, such as for example organic tissue, typically only a small number of image points of the captured pattern is available, with the result that the correspondence problem is exacerbated when using color-coded triangulation in surgery.